Abstract The objective of this study is to describe and quantify age-specific individual social contact and mixing patterns of school-aged children (K-12) in Utah across community setting over a period of a year using subjective and objective quantitative assessment. The purpose for collecting these data is to improve precision and accuracy of contact rate estimation and parameterization for infectious disease transmission models to support the development of disease prevention and control strategies. The data generated from the study will be in the form of individual contact data, social contact and mixing data, and for use in contact matrices and networks. These will be collected, processed, compared to assess agreement, and made available in forms useful for infectious disease transmission models. The study team includes expertise in various transmission modeling techniques and applications. The community settings included in the study are schools, camps, households, club meetings, and sports practices. The schools are selected to represent the demographic and climatic variability of Utah including stratification for rurality, average seasonal temperature, population density, ethnicity, socioeconomic status, and natural catchment area of the school. The study team includes expertise in collaborating with schools, statistics, GIS, epidemiology, and public health. The study will collect contact and mixing data throughout the year using seasonal blocks in the design. A subset of the school setting respondents will be recruited to participate during all four seasons. The quantitative assessment tools used to collect contact and mixing data are surveys, self-diaries, and proximity sensors. Use of subjective surveys and self-diaries is standard practice but we will deploy them in greater numbers across a broad demographic. The study team includes expertise in survey design. Use of proximity sensors is new to the field for collecting objective contact and mixing patterns. After minimal preparation of sensors for use quickly, we will continue development of sensor technology to reduce the measurable distance. The development will retain both measurement types to allow for comparable data throughout and efficient comparison of the new measurement. The study team includes expertise in wireless sensor networks, and includes the developer of the proximity sensor we will use. The design strategy includes situations where the setting population is larger than the number of sensors we will have. Optimal network sampling strategies will be developed along with estimation of network properties and prediction of contacts. The study team includes expertise in sample design and network graphs. Finally, the study includes a plan to collect influenza-specific RT-PCR test results and intervention information on a subset of the study participants in the event of an acute outbreak of influenza-like illness. The study team have expertise in pediatric respiratory disease surveillance.